Role of CIMT, eGFR, and Serum HbA1c in Predicting CAD in Non-Diabetic Patients Undergoing Elective Coronary Angiography

Abstract

Background: Pre-diabetic state, renal function, atherosclerosis burden are the major predictors for development of coronary artery disease (CAD). Present study aims to analyze the role of carotid intima-media thickness (CIMT), glomerular filtration rate (eGFR) and serum glycosylated hemoglobin (HbA1c) levels in predicting CAD on coronary angiography in non-diabetic patients. Methods: CAD and its severity according to SYNTAX score (SX score) was evaluated in 450 non-diabetic patients hospitalized with acute coronary syndrome or stable angina and underwent coronary angiography. CIMT, eGFR, and serum HbA1c values were obtained during admission. Spearman correlation and linear regression were used in the analysis of the data. Receiver operating characteristic (ROC) curve was constructed to calculate cutoff values, area under curve (AUC), sensitivity and specificity. Results:Statistically significant positive correlation was observed between HbA1c (r: 0.242, p = 0.001); CIMT (r: 0.231, p = 0.001), patient’s age (r: 0.148, p = 0.002) and SX score, whereas eGFR was negatively correlated (r: -0.148, p = 0.002). On regression analysis, CIMT, eGFR, HbA1c and patient’s age collectively predicted 36% of change in the SYNTAX score. Patient’s age > 56 years (AUC = 0.622), CIMT > 0.86 mm (AUC = 0.642), HbA1c > 6 (AUC = 0.620), eGFR 2 (AUC = 0.601) were the cutoff values on ROC curve analysis. CIMT, HbA1c had relatively high specificity (88.5%, 90.2% respectively) and eGFR had relatively high sensitivity (71.3%) among the studied variables in predicting CAD in present study. Conclusions: CIMT, HbA1c, eGFR and patient’s age at the time of admission predict CAD in non-diabetic patients undergoing coronary angiography.